TW201830298A - Delivery planning system, delivery planning method and program - Google Patents

Abstract

In the delivery problem of delivering deliveries to demanded delivery sites, the delivery planning system including a dividing unit configured to divide the delivery problem indicated by the initial condition into smaller delivery problems with a smaller scale on the basis of information on demand and supply for each delivery base included in the initial condition or information on delivery limit time of the deliverable, and a delivery plan generating unit configured to generate a delivery plan for delivery problems after the dividing unit has divided.

Description

Distribution planning system, distribution planning method and program

[0001] The present invention relates to a delivery planning system, a delivery planning method, and a program.案 This case claims priority based on Japanese Patent Application No. 2016-213838 filed in Japan on October 31, 2016, and incorporates its contents here.

[0002] The demand for car sharing is increasing. The so-called car sharing is a system in which a vehicle is shared between members, etc., the cost is paid according to the time of boarding, etc., and the vehicle is used when they like it. As one form of car sharing, there is a use form called a drop-off type (oneway type). In the car-sharing type of get-off, the user can use a common vehicle to a predetermined parking lot near the destination, and just get off the car in the parking lot to leave the car. In this form of car sharing, the vehicles used by the users must be distributed to other parking lots that have new demand for use. [0003] In order to carry out after-sales service for products purchased by customers, service personnel will visit customers. In the case of so-called after-sales service tours, the same thing will happen to the movement of service personnel and parts necessary for service provision. . For example, a plurality of customers are provided with products targeted for after-sales service, and the service staff will collect and use the after-sales service parts of the product at a certain place and carry them to the customer, or perform a variety of various activities on a single tour After-sales service staff of different types will move from a customer who needs the same parts to other customers in the provision of services, and then return the used parts to the original scene. It is necessary to choose an efficient patrol method. [0004] In response to such a problem, for example, Patent Document 1 discloses a technique for creating a transportation plan. The transportation plan uses a plurality of transportation means from a plurality of distribution bases to deliver the goods at a specified date and time. Ship to multiple delivery locations. If this technology is used, in the case of car sharing, a transportation plan for loading a vehicle used by a user on a transportation means such as a truck to each parking lot can be created. In the after-sales service tour, it is also possible to create a delivery plan for delivering parts used in service to customers. [0005] However, in the case of a car sharing delivery vehicle, a delivery method exists in which a delivery person rides on a delivery target vehicle and drives a vehicle to a destination parking lot. The method of picking up and delivering the goods on the delivery itself is called boarding transportation. In the case of delivery including boarding transportation, the technology to perform an optimal delivery plan is not provided. In the after-sales service tour, the situation where service personnel move parts, or when a part is delivered from a customer to other customers, or when the service staff carries excess parts to the next customer, etc. Similarly, the technology for performing the optimal tour plan for service personnel is not provided. Generally, the optimization problems of the combination of discontinuous values are mostly solved by a method called linear relaxation, that is, once the problem is replaced with a continuous value problem, the optimal solution method is used to obtain the optimal solution, but such as distribution As problematic, once there are many complicated restrictions, the calculation time will be too much, so we need to find a solution in practical time. [Prior Art Document] [Patent Document] [0006] [Patent Document 1] Japanese Patent Laid-Open No. 2013-136421

(Problems to be Solved by the Invention) 000 [0007] The applicant of this case has applied for a distribution planning system (Japanese Patent Application No. 2016-051550), which can solve the problem of distribution including the boarding and transportation described above. Issues in the delivery plan. By using this delivery planning system, it is possible to obtain an optimal delivery plan for a delivery problem including boarding transportation in a practical time. Regarding this distribution planning system, even if the scale of the problem becomes larger due to an increase in the number of vehicles or distribution destinations, the optimal distribution plan can be obtained in practical time, and it is expected that the calculation time will be further shortened. . [0008] Accordingly, the present invention aims to provide a distribution planning system, a distribution planning method, and a program that can solve the above-mentioned problems. (Means to Solve the Problem) [0009] According to the first aspect of the present invention, the distribution planning system includes: (i) a division unit that solves the problem of distribution of distribution items to a distribution point where necessary; The distribution problem shown in the initial conditions is divided into smaller-scale distribution problems; and the distribution plan generation unit generates a distribution plan for the distribution problem divided by the aforementioned division unit.分割 By dividing a large-scale distribution problem into small-scale distribution problems, and calculating a distribution plan in units of small distribution problems, a distribution plan can be generated in a practical time. [0010] The segmentation unit according to the second aspect of the present invention is a demand point included in a distribution base group that requires the distribution item and one included in a distribution base group that becomes a supply source of the distribution item. Supply points are attached in such a way that the moving time from the one need point to the one supply point is minimized, and a set of the corresponding combination of the aforementioned need point and the aforementioned supply point is generated, and the aforementioned initial conditions are set. The illustrated distribution problem is divided into a distribution problem from the demand point group contained in the aforementioned generated set to the supply point group. Based on the needs and supply information of each distribution base included in the initial conditions, the distribution area is divided into distribution area units of a collection of each distribution base that exists at a close distance, and the distribution plan is calculated based on the divided distribution area units. , So that you can generate delivery plans in a practical time. [0011] The above-mentioned division unit of the third aspect of the present invention calculates a movement from one supply point to one required point among the correspondence between the complex supply point and the complex demand point included in the generated set. The distribution route from the supply point to the required point when the time becomes less than a predetermined value. The distribution plan generation unit uses the moving point from the supply point group contained in the generated set to the distribution path of the required point group to become The delivery route below the predetermined critical value generates a delivery plan for the aforementioned small-scale delivery problem. Since the distribution plan is generated by using the information of the distribution path between the distribution bases whose movement time becomes below the critical value, the calculation amount necessary for generating the distribution plan can be reduced. [0012] The division unit according to a fourth aspect of the present invention obtains a plurality of preset delivery routes that indicate that a part of the delivery sites are to be delivered from the starting point and returned to the starting point, and the delivery is performed using the delivery. The unit route information of the cost at the time of route distribution is calculated from the combination of the plurality of unit route information. The number of the distribution bases contained in the combination is within a predetermined number, and the total of the aforementioned costs becomes the smallest combination. The combination of the starting point and the distribution point included is combined, and the distribution problem shown in the initial condition is divided into a distribution problem from the required point group contained in the generated set of the starting point and the distribution point to the supply point group. Based on a certain starting point, calculate the combination that meets the needs of a plurality of distribution points within a predetermined number and the distribution cost forms the smallest distribution path, and use the combination of these plural distribution points and the starting point as one distribution area. The distribution area that targets all the distribution bases given in the initial conditions is divided into the distribution areas generated in this way, and the distribution plan is calculated by the distribution area unit, so that the distribution plan can be generated in a practical time. [0013] In the fifth aspect of the present invention, the division unit calculates a combination of the unit path information by a row generation method.列 By using the column generation method, the delivery area can be generated at high speed. [0014] The division unit according to a sixth aspect of the present invention divides the distribution restriction time of the distribution item into a plurality of times, and divides the distribution problem indicated by the initial condition into each of the divided times. The distribution problem The distribution plan generation unit is based on the distribution status of the distribution items at the first time of each time after the division, to generate as many distribution items as possible to each of the division time. Delivery plans such as required locations. [0015] According to a seventh aspect of the present invention, the delivery plan generation unit is concerned with the delivery problem at the last time that is caused by the division by the division unit, and the delivery item is delivered to the location at the end of the last time. A delivery plan is generated in all the ways of the necessary delivery bases shown in the aforementioned initial conditions. According to the sixth and seventh forms, by dividing the delivery restriction time given in the initial conditions, the delivery plan is calculated for the delivery problem of the divided time unit, and the delivery plan can be generated at a practical time. [0016] The division unit according to an eighth aspect of the present invention divides the distribution problem indicated by the initial condition into a first distribution restriction that is shorter than a predetermined time included in the initial condition by a predetermined time. Time is a distribution problem of a new distribution time limit. The aforementioned distribution plan generation unit generates distribution plans such as the above-mentioned distribution items are delivered to as many locations as needed within the first distribution limitation time. [0017] In the ninth aspect of the present invention, the division unit sets a predetermined length of time following the first distribution restriction time as the second distribution restriction time. The distribution plan generation unit generates: 2. The delivery items mentioned above shall be delivered to as many distribution sites as needed within the time limit for delivery. [0018] The delivery plan generating unit of the tenth aspect of the present invention generates the start time at the end time when the delivery plan generated above is executed, and uses the start time of the first delivery restriction time as a reference, Taking the time at which the delivery restriction time included in the aforementioned initial conditions elapses as the last time of the end time, the delivery plan for the delivery of unfinished delivery items is completed as a result of the execution of the delivery plan. According to the eighth to tenth forms, the delivery restriction time is set to a time shorter than the delivery restriction time given in the initial conditions, and a delivery plan is generated while the delivery restriction time is extended. By dividing the distribution problem shown in the initial conditions into small-scale distribution problems for each set delivery limit time after extension or extension, a delivery plan can be generated in a practical time. [0019] In the eleventh aspect of the present invention, the distribution plan generation unit is configured to execute the distribution plan when a distribution plan such as a distribution point where necessary is generated as much as possible. As a result, the distribution personnel and distribution means necessary for the implementation of the aforementioned distribution plan will not remain in the aforementioned distribution base on the condition that a distribution plan is generated. It is possible to create a distribution plan such as not only delivering as many items as possible, but also redundant delivery personnel and delivery methods that are not used after the time after division. [0020] The above-mentioned distribution plan generating unit of the twelfth aspect of the present invention solves the integer planning problem based on the spatio-temporal network model composed of point information and branch information, and generates at least one involving the division by the aforementioned division unit. A collection of branch information of the aforementioned distribution problem of the divided distribution problem, the point information is a starting point and a distribution base that indicate an initial position of a distribution subject that distributes the distribution item and a distribution means that moves the distribution item or the distribution subject It is grouped with each time based on the start of delivery. 分支 The branch information refers to the above-mentioned delivery object, the above-mentioned delivery subject, and the above-mentioned delivery information between the two point information indicating the delivery of the above-mentioned delivery information among the above-mentioned point information. The flow of distribution means.模型 By modeling the distribution problem with a spatio-temporal network model, a distribution plan can be generated for a distribution problem that includes boarding and transportation. [0021] According to the thirteenth aspect of the present invention, the distribution plan generating unit is based on the spatio-temporal network model and generates, for one of the distribution bases, the entry and time of the distribution base into a group. Point information related to the entrance, point information related to the export where the outlet and time of the distribution base are grouped, and a place where the time related to the distribution is set for each of the distribution items related to the distribution base. The value of the flow of the distribution subject and the distribution of the point information between the point information related to the aforementioned entrance and the point information related to the aforementioned distribution, and between the point information related to the aforementioned exit and the point information related to the aforementioned distribution. Set to 0 or 1. By dividing the distribution base into a storage place for each of the entrance, exit, and distribution items, the status of each of these places can be represented by 0 and 1. Therefore, the distribution base can be set to a 0-1 integer. Drawing problem processing can speed up calculation processing. [0022] According to the fourteenth aspect of the present invention, it is a distribution planning system, and the distribution problem shown in the initial conditions is divided into smaller scales in the distribution problem of distributing the distribution items to the required distribution bases. For the distribution problem, a distribution plan method for generating a distribution plan for the aforementioned divided distribution problem. [0023] According to the fifteenth aspect of the present invention, the program is used to make the computer of the distribution planning system function as the following means. (1) In the distribution problem of distributing the distribution items to a distribution point where necessary, set the initial conditions. The illustrated distribution problem is divided into smaller distribution problems, and 手段 means for generating a distribution plan for the aforementioned divided distribution problems. [Effects of the Invention] [0024] According to the above-mentioned distribution planning system, distribution planning method and program, a distribution capable of minimizing the cost or moving time relative to a large-scale distribution problem in a practical time can be formulated. plan.

[First Embodiment] Hereinafter, a delivery planning system according to an embodiment of the present invention will be described with reference to FIGS. 1 to 13. FIG. 1 is a functional block diagram showing an example of a delivery planning system according to the first embodiment of the present invention. In this embodiment, the delivery planning system is configured by, for example, a computer device such as a PC or a server device. The computer device is composed of a computing unit such as a CPU (Central Processing Unit), a memory unit such as ROM (Read Only Memory), RAM (Random Access Memory), HDD (Hard Disk Drive), and other hardware such as a network interface. . [0027] The delivery planning device 10 of FIG. 1 is an example of a delivery planning system. The delivery planning device 10 is a device that calculates delivery methods, delivery routes, and the like that minimize costs for delivery plans that include boarding and transportation. In the present embodiment, a method of formulating an optimal distribution plan for realizing the distribution is given as an example of a scenario in which a vehicle commonly used by a user is delivered to a place where the user starts to use it in a drop-off car sharing type. In the case of delivery, for example, it is required to select a delivery method and a delivery route that minimize costs. The formulation of a distribution plan that minimizes costs is to date a variety of methods being provided. However, the delivery of car-sharing vehicles is different from the case of delivering goods such as courier. That's the point where people can ride on vehicles when they are being delivered. For example, in each of the sites A, B, C, D, and E, there is a state where the vehicle is redundant or insufficient. In such a state, in order to move the vehicle from the excess base of the vehicle to the insufficient base, in accordance with the needs of the user, for example, the following methods can be considered. (1) A one-person delivery person patrols each site with a truck capable of loading a vehicle, loads excess vehicles on the truck, and delivers to an insufficient site. (2) A plurality of delivery personnel board the delivery vehicle and move to each base. When a part of the delivery staff boarding the delivery vehicle arrives at a redundant location of the vehicle, they transfer to the remaining vehicle and drive the vehicle to a location where the vehicle is insufficient (boarding transportation). In such a case, it is not easy to know which delivery method is preferred for distribution, and what route is used for distribution to minimize the cost. The delivery planning device 10 of this embodiment introduces a mathematical model or limitation based on mathematical insights into the delivery plan during boarding and transportation, thereby providing a high-speed and efficient generation of a delivery plan that minimizes costs, for example. method. When the delivery plan device 10 of the present embodiment generates a delivery plan for delivering a delivery item to a delivery base, the required number of delivery items (insufficient number) for each delivery base is given based on the initial conditions for the delivery. And the supply quantity (excess quantity) to divide the entire distribution problem shown in the initial conditions into partial small-scale distribution problems. Thereby, even if the number of vehicles or bases to be distributed is large-scale, a delivery plan can be prepared in a practical time (for example, 10 minutes). [0028] As shown in FIG. 1, the delivery planning device 10 includes an initial condition setting unit 11, a delivery plan generating unit 12, an input / output unit 13, a first region dividing unit 14, and a memory unit 15. The initial condition setting unit 11 is such that a delivery entity (for example, a delivery person) can ride a mobile delivery object (for example, a vehicle used by a user), a delivery entity, a movable delivery object, or a delivery means (for example, a delivery vehicle such as a truck). ) At any of the places where the company stays, the required quantity and quantity of goods delivered, and one or more starting points (e.g., companies that provide car-sharing services) that indicate the initial location of the delivery subject and the delivery means. Use the information of the base), the information of the available distribution methods and the main body of the departure base, and the information of the delivery deadline, etc. as the initial conditions for generating the distribution plan. These parameters are explained in detail later. The distribution plan generation unit 12 calculates point information and branch information, and generates at least one set of branch information for the case where the required number of items to be distributed within the delivery period is delivered to the distribution base where the required number is set. It is a set of the distribution base and the starting base and the time based on the start of distribution. The branch information is the indication between the two point information related to the distribution among the point information, the distribution object, the distribution subject, and the distribution. Means traffic. Departure bases and distribution bases are collectively referred to as bases. The input / output unit 13 accepts an input operation by a user. The input / output unit 13 outputs, to a display or the like, information such as a delivery plan based on a set of branch information generated by the delivery plan generation unit 12. The first area dividing unit 14 is a demand point included in one of the distribution base group that needs to be delivered, and a supply point included in one of the distribution base group that becomes the source of supply of the distribution, so that the demand point from the one is included. Attach the correspondence in such a manner that the moving time to the one supply point becomes the smallest, and generate a set of the corresponding combination of the demand point and the supply point. That is, the first area dividing unit 14 divides all the delivery problems of all delivery base groups that need to be delivered according to the initial conditions into all the delivery area unit delivery problems shown in the generated collection (from the collection location). (Including the distribution of the required point group to the supply point group). Then, the delivery plan generation unit 12 generates a collection of branch information for each of the divided small-scale delivery problems. The storage unit 15 is information necessary for generating a delivery plan. The initial condition setting unit 11, the delivery plan generation unit 12, and the first area division unit 14 are executed by reading a program from the memory unit 15 by using a CPU (Central Processing Unit; central processing unit) included in the delivery plan apparatus 10, for example. achieve. [0029] The delivery planning device 10 uses a spatio-temporal network model to generate a delivery plan for a given delivery problem. First, a description will be given of a spatio-temporal network model and a method for generating a distribution plan using the spatio-temporal network model. Then, a description will be given of a method for segmenting a distribution problem when the related problem forms a large scale. [0030] FIG. 2 is a diagram illustrating an example of a delivery plan according to the first embodiment of the present invention. A description will be given of a delivery example (vehicle) of a car-sharing type shared car using a get-off and departure type using FIG. 2. In FIG. 2, the center is a base (departure base) where a delivery person of the delivered item exists and starts delivery of the delivered item. The parking lot A, the parking lot B, and the parking lot C are bases (delivery bases) that serve as a source of delivery or a destination for delivery. The user of the delivered item makes a reservation of the delivered item using a predetermined reservation system or the like. The user inputs information such as the number of uses of the delivered items, the use start location (for example, parking lot B), and the like from the reservation system. When the user wants to use the delivery from the parking lot B, if the delivery already exists in the parking lot B, the user can use the delivery. However, when the delivery does not exist in the parking lot B, the delivery person needs to move the delivery to the parking lot B from another parking lot. In the car-sharing type of alighting and alighting, for example, when a user uses a delivery from the parking lot B to the parking lot A, the user takes the delivery to the parking lot A and leaves. Therefore, a large number of users can be used, for example, a situation in which the distribution items are spread throughout the parking lot A. The distribution staff at the center distributes the general distribution to parking lot A ~ parking lot C with the needs of users. In the case of the example of FIG. 2, there are more than two delivery items in parking lot A, and less than one each in parking lot B and parking lot C. The delivery staff at the center will distribute one of the two excess items in parking lot A to each of parking lot B and parking lot C. Users can use the delivered items as desired. FIG. 2 shows an example of the realization of delivery that meets this condition. [0031] First, from the center, two delivery personnel (k, l) boarded a single delivery vehicle 1 (delivery means) and moved toward the parking lot A (1). In the parking lot A, the delivery person k moves to the parking lot B on the delivery of one of the two excess cars. The other delivery persons 1 board the delivery car 1 and move toward the parking lot B (2). In the parking lot B, the delivery person k stops the delivery item in the parking lot B and rides on the delivery vehicle 1 driven by the delivery person 1. The delivery personnel k, l return from the parking lot B to the parking lot A (3). Upon returning to the parking lot A, the delivery person k moves to the parking lot C while boarding the extra one. The delivery person 1 rides on the delivery vehicle 1 without any change and moves toward the parking lot C (4). In the parking lot C, the delivery person k stops the delivery in the parking lot C, and rides on the delivery vehicle 1 driven by the delivery person 1. The delivery personnel k, l return from the parking lot B toward the center (5). If such a procedure is used for distribution, the user's requirements can be met. In this embodiment, the distribution method of the distribution items in such a situation is formalized as the problem of the minimum cost flow of the spatio-temporal network model, and the method of minimizing the cost formation among the feasible distribution methods is obtained. [0032] <First Spatio-temporal Network Model> FIG. 3 is a diagram illustrating a first spatio-temporal network model of a distribution plan according to the first embodiment of the present invention. FIG. 3 is a diagram modeling the embodiment of delivery described in FIG. 2 into a space-time network. The vertical axis in FIG. 3 indicates the passage of time, and the horizontal axis indicates the locations of the bases. In the figure, the points in space-time are the bases representing each time. In the figure, the arrows connecting the two points indicate the movement in time and space of the delivery object, the delivery vehicle (delivery means), and the delivery person (person). Each arrow indicates the time required to move the source base and the destination. A solid line arrow indicates movement between the bases, and a double line arrow indicates a delivery item, a delivery vehicle, and a delivery person (moving time) staying at the same base. Each element attached to the row indicated by each arrow indicates the number of delivery items, delivery vehicles, and delivery personnel moved by the delivery indicated by the arrow. The number of delivery vehicles and the number of mobile delivery personnel. For example, in the case of a solid arrow 31, from the center to the parking lot A, there are 0 delivery items, 1 delivery car, and 2 delivery personnel, and the movement from time t = 0 to t = 1 is displayed. Double line arrow 32 is in parking lot A, there are 2 delivery items, 0 delivery cars, 0 delivery personnel, and it shows the situation of staying from time t = 0 to t = 1. In the case of a solid arrow 33, from the parking lot A to the parking lot B, there is one delivery, one delivery car, and two delivery personnel, and the movement from time t = 1 to t = 2 is displayed. The double-line arrow 34 is in parking lot A, with one delivery item, zero delivery vehicles, and zero delivery staff, showing the situation of staying from time t = 1 to t = 2. The number of items in parking lot A changed from two to one because the delivery staff boarded one of the two items and moved to parking lot B. The same goes for the other arrows. One arrow is called a branch. The set of branches in FIG. 3 corresponds to the delivery planner described in FIG. 2. When delivering goods, there may be time-related actions such as which parking lot is waiting for the delivery staff or the means of delivery. Most of the existing mathematical models related to the distribution plan are modeled based on the bases and the movement of the delivery vehicle between the bases as a branch. In this embodiment, a two-dimensional space-time network is used for modeling. As a result, not only the spatial movement between the bases, but also the movement of the vehicle or person involved in the time can be displayed. [0033] <Generation method of distribution plan based on first spatio-temporal network model> In this embodiment, the distribution plan is determined to meet the needs within a limited time as described in FIG. 2 and FIG. 3 A distribution plan that minimizes the cost of distribution. This problem can be formulated as the integer program problem shown below. [Objective function] Minimize the total cost of the items, means, and personnel spent on delivery [Restrictions] (1) The flow of each site is in compliance with the flow preservation rules. (2) The number of vehicles existing in the parking lot is not more than the parking space of the parking lot. (3) There must be a delivery person outside the departure point. (4) When moving, there must be a delivery person in the delivery or the delivery means. The number of people when moving is less than the total number of people who can ride on the delivery or the delivery means. [0034] In order to understand the above-mentioned integer planning problem, the delivery plan generation unit 12 generates the two-dimensional space-time information as illustrated in FIG. 3 based on the initial condition information accepted by the initial condition setting unit 11. The branches between the distribution points generate a collection of branch information such that the distribution items can be distributed to the points where the required number is set in a manner that meets the required number of each point within the delivery period. Then, the delivery plan generation unit 12 selects a set of branch information that minimizes the cost from a set of plural branch information. [0035] The mathematical model or program of the delivery plan provided so far is limited to the case where the delivered items are delivered on a transportation means such as a truck or a railway. As with the delivery of vehicles, even in the case of existing transportation, it is possible to solve the problem by adding restrictions, but it is conceivable that not only the restrictions become complicated, but also the number of combinations of means or routes will be exponentially functional The ground is increased, so it is not practical. According to this embodiment, when a distribution plan for a deliverable that can be transported on board is generated, the minimum cost flow problem as a spatio-temporal network model can be formalized to obtain the least costly distribution among the feasible distribution methods. plan. [0036] <Second Spatio-Temporal Network Model> In the second spatio-temporal network model, charts (point information and information indicating distribution personnel, items, and means of distribution) in the distribution base are added to the first space-time network model. Branch information for mobile). In this way, you can set the distribution base to a 0-1 integer planning problem. The 0-1 integer programming problem is the integer programming problem to limit the magnitude of the variables, which can constitute a tense relaxation problem. This makes it easy to put in an effective inequality (cut), and speeds up the calculation process (reduces the calculation time). [0037] When the distribution plan generating unit 12 uses the second spatiotemporal network model to generate a distribution plan, in addition to the spatiotemporal information described in the case of the first spatiotemporal network model, it also generates, for one distribution base: The point information in which the entrance and time of the distribution base are grouped, the point information in which the exit and time of the distribution base are grouped, and the point information in which the time is grouped for each of the items related to the distribution base. The delivery plan generation unit 12 sets the value of the flow rate of the delivery person and the delivery item between the point information related to the entrance and the point information related to the delivery item to 0 or 1. The delivery plan generation unit 12 sets the value of the flow rate of the delivery person and the delivery item between the point information related to the exit and the point information related to the delivery item to 0 or 1. [0038] Here, parameters related to the delivery plan preparer's input to the delivery plan device 10 will be described. The input parameters are the following items. That is, the set of departure bases (Depot), the set of delivery bases (W), the delivery deadline (dl), the time within one interval (h), the set of types of deliveries (P), and the set of types of delivery means ( D), the loading amount of the delivery means (cp), the cost of the delivery item cx (yen / minute), the cost of the delivery means cy (yen / minute), the cost of the delivery staff cz (yen / minute), the moving time Matrix M (for example, the moving time from the distribution site w1 to w2 by the distribution means d is set to m [d] [w1] [w2]), the supply quantity of each site is supply (for example, The supply quantity is set to supply [w, d]), and the required quantity of each distribution site is demanded (for example, the required quantity of d for the distribution site w is set to demand [w, d]). The initial condition setting unit 11 obtains these parameters and sets the initial conditions for the delivery plan. [0039] As an output item, the delivery plan generation unit 12 is a flow x ((v, s), (w, t)), a delivery means that distributes the goods flowing through the space-time network of the optimized delivery plan. The flow y ((v, s), (w, t)) and the flow z ((v, s), (w, t)) of the delivery person are output to the input / output unit 13. Let ((v, s), (w, t)) be a departure from the delivery site v at time s, and reach a delivery site w at time t. The output items are other costs that have been spent on distribution, etc. 4 is a first diagram illustrating a second spatiotemporal network model of a delivery plan according to the first embodiment of the present invention. The second space-time network will be described using FIG. 4. In the following, the place set is set to N, the time set is set to T, and the graph of the spatiotemporal network is G = (V, E). V is the set of points and E is the set of branches. The point set V is defined as follows. V = {(w, d, p, t) | w∈W, d∈ {0} ∪P, p∈S _wd , T ∈ T} Here, S _wd = {0,1} (d = 0), S _wd = {0,1, ..., m} (d ≠ 0). d = 0 is the road representing the entrance to the delivery base. When d = 0, S _wd Is a value of 0 or 1, S _wd = 0 means entrance, S _wd = 1 means exit. When d ≠ 0, d is the type of the delivery, S _wd It is a value from 0 to m. m is the supply quantity -1 or the required quantity -1 of the distribution base w for the distribution item d. For example, if there are more than three deliveries a at the delivery site w (supply quantity = 3), S _wd The values are 0, 1, and 2. For example, when there are less than 4 items (a required number = 4) at the distribution site w _wd The values are 0, 1, 2, and 3. For a distribution base w, a point with d = 0 is also called a road, and a point with d ≠ 0 is called a port. The stop is a place where one delivery item d is placed. 4 is Depot = {0}, W = {1,2}, P = {a}, T = {0,1,2}, S _1a = {0} (1 supply quantity for delivery item a at delivery base 1), S _2a Spatio-temporal network in the case of {0} (1 required quantity for delivery item a at delivery site 2). Next, the branch set E will be described using FIG. 5. 5 is a second diagram illustrating a second spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. Hereinafter, the branch set E is set to E = E. _x ∪E _y ∪E _z . E _x Is the branch collection of the distribution, E _y Is a collection of branches of the distribution means, E _z It is a branch collection of delivery personnel. Branch set E of the delivery _x It is defined as follows. E _wwx It is a collection of branches showing the movement between the bases of the delivery, E _wx It is a collection of branches (waiting, etc.) of the road where the distribution goods stay at the distribution base, E _wpx Is a collection of branches that represent a delivery moving from a road to an order, E _pwx Is a collection of branches that represent a delivery moving from the stop to the road, E _px A collection of branches where the distribution stays at the order. [0043] Branch Set E of the Distribution Means _y It is defined as follows. E _wwy A set of branches representing the movement between the bases of the delivery means, E _wy It is a collection of branches (waiting, etc.) of the road where the distribution means stays at the distribution base, E _wpy Is a collection of branches representing the delivery means moving from the road to the stop, E _pwy A collection of branches that represent a delivery method moving from a stop to a road. [0044] Branch set E of delivery person _z It is defined as follows. E _wwz It is a set of branches representing the movement between the bases of the delivery person, E _wz It is a collection of branches (waiting, etc.) of the road where the delivery person stays at the delivery base, E _wpz Is a collection of branches representing delivery people moving from roads to stops, E _pwz A collection of branches representing delivery people moving from a stop to a road. [0045] FIG. 5 shows an example of a branch set after the above definition. The diagonal solid arrow indicates that it corresponds to E _wwx , E _wwy , E _wwz Branches of each collection. The double arrow in the vertical direction indicates that it corresponds to E _wx , E _wy , E _wz Branches of each collection. The two-point line arrow in the horizontal direction indicates that it corresponds to E _wpx , E _wpy , E _wpz Branches of each collection. A point-locked arrow in the oblique direction indicates that it corresponds to E _pwx , E _pwy , E _pwz Branches of each collection. The dotted arrow in the vertical direction indicates that it corresponds to E _px Branch of collection. In the second space-time network model, the distribution base is set to be an integer of 0-1. However, the branches of the two-point lock line arrow in the horizontal direction, the one-point lock line arrow in the oblique direction, and the dotted arrow in the vertical direction are branched with This 0-1 integer is related to a problem, and a branch is added in this embodiment. 6 is a third diagram illustrating a second spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. The flow vector set for each branch will be described using FIG. 6. As shown in FIG. 6 (a), a flow vector is set in each branch e. [0047] [0048] Among this traffic vector, x [d, e] (d ∈ P, e ∈ E _x ) Is the flow rate of the distribution, y [d, e] (d ∈ D, e ∈ E _y ) Is the flow representing the distribution means, z [e] (e∈E _z ) Is the flow of delivery personnel. Give a few examples. In the case of P = {a} and D = {car}, the flow vector becomes as follows. [0049] [0050] The branch e shown in FIG. 6 (b) indicates a movement of a, a delivery vehicle (vehicle), and a delivery person (person). When P = {a, b}, D = {car, motorcycle}, the flow vector becomes as follows. [0051] [0052] The branch e shown in FIG. 6 (c) indicates that a is one, b is one, a delivery car (vehicle) is one, a motorcycle is one, and a delivery person (person) is two people. . 7 is a fourth diagram illustrating a second spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. FIG. 7 is a flow vector as follows, [0054] [0055] A spatio-temporal network model when one distribution object a is moved from the distribution base 1 to the distribution base 2. First, two delivery personnel (persons) and one delivery vehicle (car) will move from the Depot exit to delivery base 1 (solid arrow 91). At delivery base 1, one delivery person will move toward the storage location of delivery item a (stop 0) (two-point lock arrow 92). At stop 0 of delivery item a, delivery item a will exist until time 0 to 1 (dotted arrow 93). Next, one delivery person and one delivery item a1 will move toward the exit of the delivery base 1 (one-point lock arrow 94). Next, one delivery a, one delivery car, and two delivery staff will move from the exit of delivery base 1 to the entrance of delivery base 2 (solid arrow 95). Next, one delivery person and one delivery item a1 will move to stop 0 of delivery base 2 (two-point line arrow 96). Next, one delivery person will move from the stop 0 to the exit of the delivery base 2 (1 point line arrow 97). Next, two delivery personnel and one delivery vehicle will move from the exit of delivery base 2 to the entrance of Depot (solid arrow 98). At stop 0 of delivery base 2, delivery item a will exist until time 2 to 3 (dashed arrow 100). As shown in FIG. 7, in this embodiment, distribution points 1 and 2 are assigned to each distribution object a1, and the distribution points are assigned to the entrance and exit of the distribution point. Therefore, the value of each element of the flow vector in the distribution base 1 and the distribution base 2 becomes 0 or 1. In this way, setting the distribution base to a 0-1 integer planning problem can reduce the calculation time. 8 is a fifth diagram illustrating a second spatiotemporal network model of a delivery plan according to the first embodiment of the present invention. FIG. 8 illustrates a first spatiotemporal network model illustrated in FIG. 3 using a second spatiotemporal network model. In FIG. 8, the point set of each column of (1, 0, 0, 0), (1, a, 0, 0), and (1, a, 1, 0) which are more subdivided is shown in FIG. 3. The set of points shown in the column of parking lot A. The same applies to parking lot B and parking lot C. Each of the center, parking lot A to parking lot C is a set of points assigned to the entrance and exit. [0057] <Generation Method of Delivery Plan Based on Second Spatio-Temporal Network Model> The above explained the problem of setting the distribution base to a 0-1 integer plan as the speeding up of the processing of the second spatio-temporal network model. Countermeasures. Next, a method for generating a delivery plan will be described. As a delivery means, each of the case of delivery by a delivery vehicle and a bicycle (including the case of delivery by a delivery vehicle only), and the case of delivery by a truck (load delivery) will be described. The bicycle of the delivery method is a method in which a delivery person rides on a bicycle to move to a delivery location where there is supply, loads the bicycle in the remaining vehicle there, and the delivery person drives the remaining vehicle to move to a delivery location where needed. [0058] First, the objective function will be described. In FIG. 3, a case where the cost is minimized is described as an example. Here, the case of minimizing the moving time spent on delivery also includes a description. (In the case of delivery by a delivery vehicle and a bicycle) 1. The objective function in the case of minimizing the cost of delivery is to multiply the cost per time of each of the delivery, the delivery vehicle, and the delivery staff by the moving time and add it. 2. The objective function in the case of minimizing the moving time spent on delivery is to add the moving time of each of the delivery, the delivery car, and the delivery person. [0059] (In the case of delivery by truck) 1. The objective function in the case of minimizing the cost of delivery is to multiply the cost per time of each of the delivery truck and the delivery staff by the moving time and add it. 2. The objective function in the case of minimizing the moving time spent on delivery is to add the moving time of each of the delivery truck and the delivery person. [0060] Next, the restrictions will be described. (The case of delivery by delivery trucks and bicycles is the same as the case of delivery by trucks) 1. Flow rate preservation rules (1) The flow rate of the delivery items at the delivery start time is 1. At the time when the delivery is completed, the flow into the order with the required order will become 1. At other points, outgoing traffic is equal to incoming traffic. [0061] (2) The flow rate of the delivery car is the number of points of the delivery car at the time when the delivery car starts. At the time when the delivery is completed, the traffic entering the road where the delivery vehicle is present is the number of existing delivery vehicles. At other points, outgoing traffic is equal to incoming traffic. (3) The traffic of the delivery staff At the time of delivery start, the traffic going out of the road where the delivery staff is located is the number of people who become the delivery staff. At the time when the delivery is completed, the traffic entering the road where the delivery personnel are present is the number of people who become the delivery personnel. At other points, outgoing traffic is equal to incoming traffic. 2. Capacity limit The amount of goods and people moving in the distribution base is 1 or less. [0062] 3. Restrictions in Distribution Bases 1 (E _wp (It is a collection of branches, distribution means, and people moving from the road to the stop.) (1) When the place where d goes is d, the delivery will not enter the stop from the road. (2) When the destination of e is the required point of d, the flow rate of the distribution goods and the distribution personnel shall be the same value (0 or 1). (3) In either case, the number of bicycles is less than the number of delivery staff. [0063] 4. Restriction in Distribution Base 2 (E _pw (It is a collection of distribution goods, distribution means, and branches of people moving from the stop to the road.) (1) When the starting point of e is the supply point of d, the flow of the distribution goods and the distribution personnel is the same value (0 or 1). (2) When the starting point of e is the required point of d, the delivery will not exit the stop to the road. (3) In either case, the number of bicycles is less than the number of delivery staff. [0064] Hereinafter, the case of distribution by a delivery vehicle and a bicycle and the case of distribution by a truck will be described. (For delivery by delivery vehicle and bicycle) 5. Restrictions on branches when moving from a base to another base (E _ww (It is a collection of branches that indicate the movement between a delivery, a delivery method, and a person's base.) (1) When e is a branch of a bicycle and the branch of the bicycle is moved by the bicycle and the delivery person, and the bicycle is loaded When the car is moving, it is restricted that there must be a delivery person in the car. The number of delivery personnel is less than the number of passengers that can be carried, and the number of bicycles that cannot be driven is less than the number of bicycles that can be loaded on the vehicle. (2) When e is a branch of the bicycle but is not a branch of the bicycle (moving by bicycle) The number of bicycles is the same as the number of people. [0065] 6. The restriction on branches staying in the distribution base is restricted to a certain person in the car. [0066] (In the case of delivery by truck) 5. The restriction on the branch when moving from a delivery site to another delivery site is limited to a truck that must be delivered by a delivery person. The number of delivery personnel is less than the number of passengers that can be carried. The total volume is below the loading capacity of the truck. [0067] 6. Restrictions on branches staying in distribution bases restrict the total volume of the distribution items to be less than the loading capacity of the truck. [0068] In order to reduce the calculation time, a restriction formula called a cut can be applied. In the integer programming problem, an inequality that meets the points of the feasible field is called an effective inequality. Integer planning problems are difficult to solve, so there are many linear relaxation problems that remove integer conditions first. A case where an effective inequality that reduces the solution space of a linear relaxation problem is added is called addition of cutting. With the addition of cutting, the linear relaxation solution is close to the integer optimum solution, so it has a powerful effect in speeding up the calculation. With the addition of cutting, the executable area is not cut, so the optimality of the solution is guaranteed. For example, it is added that the delivery vehicle is cut such that one or more vehicles arrive. Therefore, it is possible to exclude the unrealistic situation that the delivery vehicle is 3/4 units from the calculation object, and the calculation speed can be improved. A specific example of cutting is described in the specification of Japanese Patent Application No. 2016-051550 by the applicant of the present case. In the case of additional cutting, the integer planning problem that requires several hours or more without additional cutting can be solved in a few minutes. [0069] The distribution plan generation unit 12 generates a spatio-temporal network model that divides the distribution bases by roads (d = 0) and stops (d ≠ 0), and uses the above-mentioned restrictions and additional cuts to generate Calculate branch information. According to this embodiment, since the distribution base can be modeled as a 0-1 integer plan problem, in addition to using the first space-time network to generate the effect of the distribution plan, the distribution plan can be obtained. The effect of calculating the time required can be reduced. Furthermore, the calculation time can be greatly reduced by adding cutting. Thereby, for example, comparison of the distribution plan generated under various initial conditions enables selection of a lower-cost distribution plan, etc., and the convenience of the planner is improved. [0070] Next, an example of generating a delivery plan using the second space-time network will be described. FIG. 9 is a diagram showing an example of a delivery problem in the first embodiment of the present invention. FIG. 10 is a diagram showing an example of a delivery plan generated for a delivery problem. A point c0 (depot) in FIG. 9 is a starting point. The other points w1 to w9 are distribution bases. For example, at point w7, "d1: 2" indicates a state where there are more than two deliveries d1, and at point w5, "d2: -1" indicates a state where there are less than one deliverable d2. At 4 o'clock w2, "d1: -1, d2: 1" indicates a state where there is less than one delivery item d1 and there is one more delivery item d2. From the state where the distribution objects d1 to d3 shown in FIG. 9 are omnipresent, the problem of distributing the distribution objects d1 to d3 is considered, so that the distribution objects d1 to d3 can disappear in a state where the distribution points are insufficient. In the following, examples of distribution by a vehicle and a bicycle, and distribution by a truck are examples of a distribution plan generated by the distribution planning device 10. [0071] 1. Delivery by car and bicycle (1) Input: In the depot, there are one delivery car, three bicycles, and three delivery staff. Delivery period: 120 minutes. Cost of the delivery vehicle: 1.5 yen / minute. ･ Cost of delivery personnel: 17 yen / minute ･ Cost of d1, d2, d3: 1.5 yen / minute Number of people: 1 person, the number of bicycles: 0, ･ d2: 4 people, the number of bicycles: 1, d3: 2 people, the number of bicycles: (2) Minimize the cost of the objective function. [0072] If the above-mentioned restriction and cutting are added to this objective function and the calculation is performed in the delivery planning device 10, the next-level output result can be obtained. (3) Output: As shown in Fig. 10, there are two delivery vehicles, one bicycle, and two delivery personnel. They are divided into two delivery routes shown by S1 to S7 and two delivery routes shown by T1 to T9. Delivery. ･ Delivery cost: 2,768 yen. Required time: 60 minutes. In this way, you can obtain a delivery plan that minimizes costs within the conditions of the delivery method, delivery personnel, and delivery deadline set in the initial conditions. [0073] The distribution plan utilizing the first spatio-temporal network or the second spatio-temporal network by the distribution planning device 10 is also applicable to distribution, planning, and after-sales service tours of deliverables that can be transported. For example, in the after-sales service, after the procurement of parts necessary for the after-sales service, etc., the service must be provided to the customer or the number of customers. The distribution items can be used as parts for after-sales service, the main body of the distribution can be service personnel, and the distribution means can be used by the service personnel to transport vehicles or parts necessary for transportation, etc. For the installation place of products for customers or after-sales services, the above mathematical model is applied to solve the problem of integer planning. When a plurality of customers perform after-sales services, service personnel can calculate the cost or time of the tour. Minimal tour method (tour means, tour path). In the case of FIG. 2, for example, as long as a customer providing after-sales service is a parking lot A to a parking lot C (delivery base), a vehicle (delivery) is used as a part, and a car (delivery means) is used as a service means for a mobile worker, The delivery person (delivery subject) may be used as a service person. The situation of after-sales service is not only to tour customers, but also to perform inspections and repairs on customers. As long as the distribution planning devices 10, 10A, and 10B using the spatio-temporal network model are used, the patrol actions of service personnel can be modeled in consideration of such operation time. [0074] In addition to the above-mentioned examples, the present invention is also applicable to the delivery of items that are not transported on board. For example, there is a collection method called Milk-Run. Collective distribution refers to a method for raising a certain product manufacturer to obtain raw materials or parts used in the product from a plurality of suppliers, instead of moving the product to each supplier, but a method in which the manufacturer visits each supplier to purchase raw materials. When collecting goods by collecting goods, for example, by collecting goods by one truck, compared with the situation of delivery to each supplier, cost reduction, reduction of traffic jams around the factory, and environmental load can be achieved. Lighten. When calculating the optimal itinerary method for containerized delivery using the delivery planning device 10 of this embodiment, for example, if the factory of the orderer of a product manufacturer is used as a delivery base that requires car sharing, the delivery of raw materials or parts is required. As the factory's redundant distribution base, the manufacturer's factory can calculate the distribution plan by setting the same objective function, restriction conditions, etc. as in the case of "delivery by truck". Regarding the case of delivery by truck as described above, the restriction condition that "the total volume of the items to be delivered is equal to or less than the loading capacity of the truck" is changed to "(the weight of the raw material x the amount of the raw material + the weight of the part x the number of parts) as the loading amount of the truck Below ". When the collection time range of a certain supplier is specified, the information can be added by adding the information of the specified collection time range to the restriction. For example, when the arrival time to a certain supplier must be formed 30 minutes later (from the start of the collection), as long as the next restrictions are added, a collection plan that complies with the time limit of the supplier can be generated. After the arrival time of a certain supplier is ≧ 30 minutes [0075] Up to this point, the processing of generating the delivery plan by the delivery plan device 10 of this embodiment has been described. According to the method described above, the delivery planning device 10 can obtain a strict optimal solution to the delivery problem. However, depending on the above-mentioned method, once the scale of the problem becomes large (for example, there are 20 distribution bases and 20 vehicles are distributed), it may be difficult to solve in practical time. Then, the first area division unit 14 divides the distribution bases for each distribution area, and divides the assigned distribution problem into distribution problems for each divided area. Next, the area division process (first area division process) by the first area division unit 14 will be described. 11 is a first diagram illustrating a first region dividing process according to the first embodiment of the present invention. The left figure of FIG. 11 shows the locations of the distribution bases and departure bases in the area targeted for the distribution plan. In the figure, the dots indicate the delivery bases (w1 to w17), and the four corner points are the departure bases (c1 to c3). At the distribution bases w1 to w17, there is a need or surplus for distribution items, and at the departure bases c1 to c3, there are distribution cars or distribution personnel. The first area dividing unit 14 is a group that generates a correspondence between a nearby needful distribution site (required point) and a remaining distribution site (supply point), and further generates a group that gathers one or more need points and supply points. And a segmented area. The generation of a region by the first region dividing unit 14 is referred to as a first region dividing process. [0077] The right diagram of FIG. 11 shows a result of the first region division process performed by the first region division unit 14. The distribution sites w1 to w5 belong to the area j1, the distribution sites w6 to w9 belong to the area j2, and the distribution sites w10 to w17 belong to the area j3. The delivery plan generation unit 12 generates delivery plans for the divided regions j1 to j3 in the above-described manner, respectively. Areas j1 to j3 are small-scale distribution bases with less than 10 distribution bases, respectively. Therefore, the delivery plan generation unit 12 can use the above-mentioned spatio-temporal network model to generate delivery plans in a practical time. [0078] Next, the outline of the first region dividing process will be described using FIG. 11. First, the first area dividing unit 14 divides the distribution sites w1 to w17 into a demand site, a supply site, and a distribution site that is neither a demand site nor a supply site. Next, the first region dividing unit 14 corresponds to the need point and the supply point in a one-to-one correspondence. At this time, the first region dividing unit 14 associates those with a short distance (moving time) between the demand point and the supply point with each other. For example, at the delivery site w4 in FIG. 11, the delivery item d1 is redundant 1, and at the delivery site w5, the delivery item d1 is less than 1. At the distribution site w6, the distribution item d1 is excess 1, and at the distribution site w7, the distribution item d1 is less than 1. At the distribution site w8, the distribution item d2 is redundant 1, and at the distribution site w9, the distribution item d2 is less than 1. In this case, the first area dividing unit 14 matches the needs with the supply, and assigns a close distance between the distribution bases. That is, the first area dividing unit 14 associates the distribution site w4 with the distribution site w5 (as a group 1), associates the distribution site w6 with the distribution site w7 (as a group 2), and associates the distribution site w8 with the distribution Base w9 is attached (as group 3). The other need points and supply points are similarly attached. [0079] Next, the first region dividing unit 14 generates a region by aggregating a plurality of groups that are close to each other with respect to a group of corresponding demand points and supply points. In this case, if there is no other group at a short distance, one group may be used as one region. For example, in the example given above, the first area dividing unit 14 calculates the distance between the delivery site w4 of group 1 and the delivery site w6 of group 2. Then, if the calculated distance is smaller than a predetermined threshold, the groups 1 and 2 are classified into the same region. If the calculated distance is larger than the predetermined threshold, the groups 1 and 2 are determined as other regions. . For the calculation of the distance between groups, for example, the distance between groups 1 and 2, you can also calculate the distance between the distribution base w4 and the distribution base w7, or the distribution base w4 ~ the distribution base w6, and the distribution base w4 ~ The distances between the distribution sites w7, distribution sites w5 to distribution sites w6, and distribution sites w5 to distribution sites w7. The average of the calculated distances is taken as the distance between group 1 and group 2. Or, the maximum (or minimum) distance among the calculated distances may be used as the distance between group 1 and group 2. In the case of the example of FIG. 11, for example, the first region dividing unit 14 classifies group 2 and group 3 into the same region j2, and classifies group 1 into another region j1. The first area dividing unit 14 also performs the same processing on the other distribution sites, classifying the distribution sites w1 to w17 for each region, and generating the regions j1 to j3 shown in FIG. 11. [0080] If the area is generated by the first area division processing, the delivery plan generation unit 12 can also supply the number of deliveries to each of the delivery bases in each area for each of the areas j1 to j3. The distribution problem that requires initial quantity, such as quantity and quantity, uses the first spatio-temporal network model or the second spatio-temporal network model to generate the distribution plan. However, even if the calculation using the spatio-temporal network model is not based on the initial state, It is also possible to use the correspondence between the need point and the supply point during the first region division process as branch information. That is, the distribution plan generation unit 12 generates branch information from the corresponding need point to the supply point, and by connecting these, it is possible to generate a distribution plan that meets all needs. However, the delivery route connecting only the closest delivery sites is too limited, and the entire delivery plan moving between plural sites may be far away from the optimized state. Therefore, the first area dividing unit 14 performs a process of adding a delivery route that may be selected when the delivery plan generation unit 12 generates branch information. Then, the delivery plan generation unit 12 selects an appropriate delivery route from among all delivery routes that have been added to the delivery routes that may be added to the delivery route between the nearest delivery bases that meet the needs and supply. To generate branch information and generate distribution plans for each region. In FIG. 11, the demand point and the supply point are described as the distribution bases, but they may be respectively a demanded stop and a supplied stop. [0081] Next, the first region division processing will be described in detail. FIG. 12 is a second diagram illustrating a first region dividing process according to the first embodiment of the present invention. The processing method (algorithm) of the first region division processing in this embodiment will be described below. The first region dividing unit 14 performs each process using the following program. 1. First, each stop of each distribution base (in the case of the first spatio-temporal network model, the distribution base) is divided into a supply point and a demand point, and a set A of supply points and a set B of demand points are generated. Set to V ₁ = A∪B. 2. Secondly, at V ₁ Add new points s and t and set V = V ₁ ∪ {s, t}. 3. From A to B, make a delivery route e ₁₁ ~ e ₁₉ For each delivery route, a cost function c (e) of the moving time when the delivery is performed according to the route shown by the delivery route is defined. 4. Create a delivery route from s to A and B to t, and set these costs to zero. Let E be the set of delivery routes from s to A and B to t ₂ , Will E ₁ With E ₂ And the set is set to E. 5. Two graphs G = (V, E) are constructed by the processing so far. 6. Calculate the minimum component maximum match of G, that is, the path from s to t with the minimum cost. More specifically, among the paths from s to t, the number of distribution paths from each supply point included in set A is 1, and the number of distribution paths to each required point included in set B is 1. Next, the distribution route (main problem) where the total cost of the distribution route connecting each supply point of s and set A and each required point of set B and t is minimized is calculated. According to 4., the cost from s to each supply point in set A and the cost from each need point in set B to t are 0. Therefore, the supply point a1 to supply point a3 and the demand point when the cost is minimized can be obtained. b1 ~ Need to attach the corresponding method of point b3. Here, the cost is a function of the moving time, so a one-to-one match between the closest supply point and the required point can be obtained. In the example of FIG. 12, for example, the delivery route e connecting a1 and b1 ₁₁ To connect the delivery route e of a2 and b3 ₁₆ , Connecting the delivery route e of a3 and b2 ₁₈ The combination is the distribution path that minimizes the total cost. In this case, a1 and b1, a2 and b3, and a3 and b2 are attached one-to-one. 7. Secondly, all the stops are divided by area so that the corresponding two stops are included in the same area. At this time, if the travel time between the corresponding two stops is less than a predetermined value, the area is classified into one area. In the example of FIG. 12, for example, a corresponding area a1 and b1, a2 and b3, a3 and b2, a1 and b1 as one area (j4), and a2 and b3, a3 and b2 as 1 The region (j5) is classified. [0082] 8. Next, two graphs created by the procedures of 1. to 5. were made again to generate the relative problem of 6. (relative problems can be generated mathematically). For the branch e = (u, v), if the optimal solution of the main problem X ^* (e) is 1, then the case where the optimal solution of the relative problem is set to Y is c (e) -Y ^* (u) -Y ^* (v) = 0 (complementary slackness), c ^ (e) = c (e) -Y ^* (u) -Y ^* (v) to define c ^ (e), and make c ^ (e) have a width according to 0 ≦ c ^ (e) ≦ ε (ε is a predetermined fixed number). This condition is not only a case where c ^ (e) = 0, but c ^ (e) becomes ε or less, it also means a candidate for the delivery route. That is, a solution to the holding width can be obtained even in a case where the main problem is not only the cost formation is the smallest. With the relaxation of the conditions for this solution, in the example of FIG. 12, for example, the candidate e of the delivery route connecting a1 and b1 can be obtained again. ₁₉ . [0083] The above first region division processing is completed. Once the first region division processing is completed, the distribution plan generation unit 12 generates a distribution plan for each divided region. At this time, the delivery plan generation unit 12 generates a delivery plan that meets the conditions by using the candidates of the delivery route obtained in the first area division process. Specifically, in addition to the above "1. Traffic preservation rules" to "6. Restrictions on branches staying in distribution bases", restrictions are added to the use of the distribution route obtained in the first area division process. Alternate (e ₁₁ , E ₁₆ , E ₁₈ , E ₁₉ ) To calculate the set of branch information. [0084] Next, a flow of the process of generating a delivery plan according to this embodiment will be described. FIG. 13 is a flowchart showing an example of a delivery plan generation process according to the first embodiment of the present invention. First, a delivery person who performs a delivery plan inputs initial conditions of the delivery plan to the delivery plan device 10. The input / output unit 13 receives the input, and outputs the received information to the initial condition setting unit 11. The initial condition setting unit 11 acquires information on initial conditions input by the delivery person (step S11). The initial condition setting unit 11 sets the acquired initial condition information to the initial conditions of the delivery plan. The initial conditions are, for example, the supply quantity (excess quantity), required quantity (insufficient quantity) of the distribution items at each site, the number of delivery vehicles at the departure site, the number of delivery personnel, the movement time between the sites, and delivery. Deadline, etc. Next, the first region division unit 14 performs the first region division process by using the supply quantity and required quantity of the distribution items of each distribution base (or stop) included in the information of the initial conditions (step S12). The first region division processing is described using FIG. 11 and FIG. 12. [0085] Next, the distribution plan generation unit 12 generates the regions obtained in each of the first region division processing, and generates them in a manner consistent with the above-mentioned restrictions on the spatio-temporal network model illustrated in FIG. 3 or FIG. 8. The branch information generates a set of branch information that meets conditions such as delivery deadlines (step S13). Specifically, the delivery plan generation unit 12 generates information for the number of delivery items, the number of delivery vehicles, and the number of delivery personnel for the candidates of the delivery route obtained in the first area division process, and meets each restriction condition ( "1. Traffic retention rules" ~ "6. Restrictions on branches staying in distribution bases"). The delivery plan generating unit 12 generates branch information that is generated in combination, and generates a plurality of sets of branch information that indicate the required number of units that meet each site by the delivery deadline. [0086] Next, the delivery plan generation unit 12 calculates the total cost for each region and for each set of branch information generated (step S14). For example, for each delivery vehicle, delivery person, and delivery item, the unit cost incurred per unit time is recorded in advance in the memory section 15, and the delivery plan generation section 12 multiplies the unit cost of the delivery cart, delivery person, and delivery item. The time shown in each branch is used to calculate the cost of each branch (the total cost of the delivery car, the delivery staff, and the delivery). The delivery plan generation unit 12 calculates the total cost of each branch included in the set of branch information and adds them up. The total cost is the cost for a set of branch information. The delivery plan generation unit 12 calculates a cost for each of the sets of all branch information for each area. [0087] Next, the delivery plan generation unit 12 compares the calculated costs for each set after calculation for each area, and selects the set of branch information whose total cost is the smallest (step S15). The selected branch information set indicates the movement of the delivery item, the delivery method, and the delivery person over time based on the starting point or the state of each delivery point indicated by the initial conditions (Figs. 3 and 8). Therefore, as long as the distribution is performed based on the collection of branch information, distribution corresponding to the needs of users becomes possible. That is, the set of branch information is a distribution plan regarding the obtained 1 area after division. Once the delivery plan generation unit 12 finishes generating delivery plans for each area, delivery plans for all delivery bases that are given as initial conditions are generated. [0088] According to this embodiment, by dividing the entire distribution bases given initial conditions into a set (area) of distribution bases at a short distance, the scale of the distribution problem can be reduced, and the number of distribution sites in each area can be reduced. The calculation amount of the delivery plan generation process. The candidates for the delivery route are calculated when the area is divided, and the delivery route is selected from these candidates to generate branch information. Therefore, the amount of calculation can be further reduced. With this, even if there are a large number of items to be distributed or distribution bases, and a large-scale distribution problem occurs, a distribution plan can be generated in a practical time (for example, 10 minutes). In step S13, the delivery plan generation unit 12 may generate branch information without using the candidate of the delivery route, and generate a delivery plan. Areas can also be added to the cost of the area's delivery plan to restructure the area. For example, there may be a pair of areas where the difference in delivery costs deviates significantly. By expanding the area where delivery is completed as soon as possible and reducing the area where delivery is completed late, the overall cost may be reduced. [Second Embodiment] Next, a distribution planning system of another method (second embodiment) for generating a distribution plan at a practical time for a large-scale distribution problem will be described with reference to FIGS. 14 to 18. In the first embodiment, a small-scale area focusing on the need points and supply points that are relatively close together is created by combining a pair of demand points and supply points. In the second embodiment, the area division processing is performed centering on the starting point, and a distribution plan is generated in each divided area. The region division process of the second embodiment is referred to as a second region division process. 14 is a functional block diagram showing an example of a delivery planning system according to a second embodiment of the present invention. Among the configurations of the second embodiment of the present invention, the same reference numerals are assigned to the functional portions of the delivery planning device 10 constituting the first embodiment of the present invention, and descriptions thereof are omitted. The delivery planning device 10A of the second embodiment includes a second area dividing unit 16 instead of the first area dividing unit 14 of the configuration of the first embodiment. The second area dividing unit 16 obtains a plurality of unit route information indicating a preset delivery route and a cost when the delivery route is delivered. The preset delivery route is a part of the delivery bases from the departure base. Delivery and return to the original starting point. The second area dividing unit 16 selects a combination in which the number of distribution bases included in the combination is within a predetermined number from among a plurality of combinations of unit path information, and the cost is minimized. The set of departure bases and distribution bases included in the combination of the unit route information is a divided area. The second area dividing unit 16 is implemented by a CPU included in the delivery planning device 10A reading a program from the memory unit 15 and executing it. [0091] FIG. 15 is a first diagram illustrating a second region division process of a delivery problem according to a second embodiment of the present invention. In FIG. 15, the dots indicate the delivery base w1 to the delivery base w17, and the four-pointed corners represent the departure base c1 to the departure base c3. In this embodiment, firstly, all conceivable patterns of demand / supply are enumerated, and a plurality of simple delivery routes that meet the needs of each pattern and supply are created for each starting point. Here, there are a sufficient number of delivery vehicles (trucks) or delivery personnel at the starting point c1 to starting point c3. The delivery points w1, w3, w6, w8, and w10 are the supply points, and the delivery points w2, w5, w7, and w9, w11 is the required point. The types of items to be delivered are the same. In this case, the so-called simple delivery route that meets the needs of each departure site is, for example, departure from the departure site c1 to the delivery site w1 (R1), taking the delivery at the delivery site w1, and transporting the delivery towards the delivery site w2 ( R2), once the delivery is completed, return to the delivery route of the departure base c1 (R3) (as the delivery route 1). Similarly, the route from the starting point c1 to the starting point c1 via the delivery point w3 and the delivery point w5 (as the delivery path 2), and the return path from the starting point c1 to the starting point c1 via the delivery point w6 and the delivery point w7 (as Delivery route 3), from the starting point c2 to the starting point c3 via the delivery point w8 and the delivery point w9 to the starting point c2 (as the delivery path 4), and from the starting point c3 to the starting point c3 via the delivery point w10 and the delivery point w11. Delivery route (as delivery route 5), etc. These simple paths are created in advance and recorded in the memory unit 15. Although not shown, for example, the following paths are also recorded in the memory unit 15 in advance. From the starting point c1 to the delivery path of the starting point c1 via the delivery point w1 and the delivery point w5, from the starting point c1 to the starting point c1 via the delivery point w1 and the delivery point w7, and from the starting point c1 to the delivery point w3. And delivery point w2 to return to the starting point c1, from the starting point c1 to the starting point c1 via the delivery point w10 and the delivery point w11, to the starting point c1 to the starting point c1 via the delivery point w1 and the delivery point w2. The delivery route of c2 is a delivery route from the starting location c3 to the starting location c3 via the delivery location w1 and the delivery location w2. [0092] The so-called simple delivery route is not a single-finger delivery route that returns to the original departure point via one supply point and one need point (a route that returns to the original departure point by traversing two delivery points) It is also possible to start from the starting point c1, take 2 items at the delivery point w1, and deliver each item to the delivery point w2 and the delivery point w4, and return to the delivery path of the departure point c1 (the example is 3 delivery points) ). Or, it is also possible to start from the starting point c1, take 1 delivery item at the delivery point w1, and deliver it to the delivery point w2, and then take 1 delivery item at the delivery point w3, reach the delivery point w4, and return to the delivery path of the departure point c1 (Example of four distribution bases). [0093] FIG. 16 is a second diagram illustrating a second region division process of a delivery problem according to a second embodiment of the present invention. As shown in FIG. 16, the storage unit 15 stores a plurality of simple delivery routes prepared in advance. Correspondence is given to a simple delivery route, and the cost at the time of delivery by this delivery route is recorded. Cost is, for example, assigned as a function of travel time. The more information about the simple distribution route and cost recorded in advance, the more accurate the distribution plan (close to the strict optimal solution) can be generated. Information including the simple delivery route illustrated in FIG. 16 and the cost corresponding to the delivery route is referred to as unit route information. [0094] FIG. 17 is a third diagram illustrating a second region division process of a delivery problem according to a second embodiment of the present invention. Next, the second region division processing by the second region division unit 16 will be described with reference to FIGS. 15 to 17. The premise is that the unit path information illustrated in FIG. 16 is recorded in the memory unit 15. The initial requirements for delivery requirements (the number of delivery locations, the number of supplies, the number of delivery vehicles at the departure location, the number of delivery personnel, etc.) are given. 1. First, the second area division unit 16 reads out from the memory unit 15 the unit route information that includes a part of the delivery route among the delivery requests (required) to which the initial conditions are given. 2. Secondly, the second area dividing unit 16 is a delivery route included in the unit route information read out in combination, and creates a route that meets all delivery requirements as a tentative solution. Here, as a method of combining the simple distribution routes recorded in advance, and finding all the combinations that meet all the requirements and the cheapest cost, a mathematical method called a set partitioning method can be used. In this case, Once the number of simple delivery routes is expanded, the optimization problem of the combination may not be solved in a practical time. For this reason, the second region dividing unit 16 is a simple delivery route that is stored in the storage unit 15 by using a small number of delivery routes to generate an initial solution. A mathematical method called a column generation method is used to add simple To find the optimal solution. The few simple delivery routes used to generate the initial solution can be selected by any method. In the initial solution generation, a commonly provided solver can be used. At this time, a limit is placed on the number of distribution bases supported by one departure base (for example, including a demand point and a supply point, within 6 bases, etc.). Here, the reason for setting a limit (upper limit) on the number of distribution sites is to reduce the amount of calculation and speed up the processing. For example, the number of restricted distribution bases may be actually calculated, and the number of distribution bases may be set as an upper limit in a case where it can be solved within a practical time. The initial solution can be obtained, for example, as shown in FIG. 15 (delivery route 1 to delivery route 5). [0095] Secondly, the second region dividing unit 16 selects one or a plurality of delivery routes from the unselected simple delivery routes by a column generation method (a well-known mathematical method), and calculates that the replacement has been performed. Reduce costs when choosing a simple delivery route and a selected simple delivery route. Cost reduction refers to the total of the cost (cost column in FIG. 16) recorded corresponding to the simple delivery route selected as a re-solution by replacement, and the original simple delivery route corresponding to the original delivery route selected before replacement is subtracted. The total value of the recorded costs. [0096] 4. If the reduced cost after the calculation in 3. is a negative value (less expensive after replacement), the existing full delivery route is updated with the simple delivery route selected in 3. a part of. For example, regarding the delivery to the delivery site w7, in the initial solution shown in FIG. 15, although the delivery route 3 is selected, the second area dividing unit 16 replaces this delivery route 3 and calculates to replace the delivery route c2 via the delivery. The cost is reduced when the route w6 and the delivery site w7 return to the route (set to the delivery route 6) to the departure site c2. According to FIG. 16, the cost of the distribution path 3 is 2500, and the cost of the distribution path 6 is 1500, so the reduction cost is -1000. Therefore, the second area dividing unit 16 updates the delivery route 3 with the delivery route 6. The combination of the updated simple delivery routes is shown in FIG. 17. In the case of calculating a reduction in cost, the second area dividing unit 16 selects a delivery route so that the number of sites supported by one departure site is within the limit. [0097] This example is an example in which a simple delivery route is moved from the burden range of the departure base c1 to the burden range of the departure base c3, but the update of the delivery route is not limited to this example. For example, in the state of FIG. 15, the combination of the delivery route 1 and the delivery route 2 in the route carried by the departure base c1 may be updated to return from the departure base c1 to the departure base c1 via the delivery base w3 and the delivery base w2. A method of combining a route from the departure base c1 to the departure base c1 via the delivery base w1 and the delivery base w5. Or, there may be two target items at the delivery point w1, and the combination of the delivery path 1 and the delivery path 2 may be updated from the starting point c1 to the delivery point w1, the delivery point w2, the delivery point w3, and the delivery point w5. Method for returning the delivery route to the departure base c1. [0098] 5. The second region dividing unit 16 repeats the processes from 3. to 4., and ends the second region dividing process at a point in time when a path that can reduce costs disappears. Once the second area division process is completed, the distribution bases within the limit (for example, 6 bases) will be associated with each starting base. The set of the associated plural distribution bases and departure bases (for example, each of the area j6 to the area j8) is an area obtained by the second area division processing. [0099] Next, the flow of the generation process of the delivery plan according to this embodiment will be described. 18 is a flowchart showing an example of a delivery plan generation process according to the second embodiment of the present invention. The same processing as in FIG. 13 will be briefly described. First, the initial condition setting unit 11 acquires information on initial conditions input by a delivery person or the like (step S11). Next, the second area division unit 16 performs the second area division using the supply quantity, the required quantity, the number of delivery personnel at the departure location, and the type and number of delivery vehicles included in the information of the initial conditions. Processing (step S121). The second region division processing is as described with reference to FIGS. 15 to 17. [0100] Next, the delivery plan generation unit 12 is a region obtained in the second area division process (departure bases obtained in the second area division process and a plurality of associated delivery bases associated with the departure bases). Set), on the spatio-temporal network model exemplified in FIG. 3 or FIG. 8, branch information is generated in a manner that meets the above-mentioned restrictions, and a plurality of sets of branch information that meet the conditions such as the delivery deadline (step S131) . In the example of FIG. 17, the delivery plan generation unit 12 generates a set of branch information for each of the areas j6 to j8. The delivery plan generation unit 12 may generate branch information regardless of a simple delivery path and a combination thereof used in the second area division process, or may use a simple delivery path and a combination thereof to generate branch information. [0101] Next, the delivery plan generation unit 12 calculates the total cost for each set of branch information generated (step S14). In the example of FIG. 17, the delivery plan generation unit 12 calculates the total cost of each set of branch information generated for each of the regions j6 to j8. Next, the delivery plan generation unit 12 compares the calculated total cost and selects a set of branch information whose total cost is the smallest (step S15). In the example of FIG. 17, the delivery plan generation unit 12 selects a set of branch information having the smallest total cost for each of the areas j6 to j8. The selected branch information set is a distribution plan showing each area. That is, once the distribution plan generation unit 12 finishes generating the distribution plan for each area, the distribution plan for all the distribution bases before the division is generated. [0102] According to this embodiment, all the distribution bases that are needed or supplied in the initial condition can be associated with the departure bases one by one, so that the distribution areas can be divided into distribution areas for each departure base. By dividing the distribution area into small-scale distribution areas, the distribution plan generation process is performed for each of these distribution areas, instead of generating a distribution plan by targeting all the necessary distribution bases given in the initial conditions. In this case, it is possible to reduce the amount of calculations necessary to generate a delivery plan. With this, even when there are a large number of items to be distributed or distribution bases, and when a large-scale distribution problem arises, a distribution plan can be prepared in a practical time (for example, 10 minutes). [0103] <Third Embodiment> A distribution planning system related to another method (third embodiment) for generating a distribution plan at a practical time for a large-scale distribution problem will be described with reference to FIGS. 19 to 22. In the first and second embodiments, the distribution problem is spatially divided (area division) according to the needs and supply information of each distribution base included in the initial conditions, thereby dividing into small-scale distribution problems. A method to solve the problem of small-scale distribution and achieve high-speed processing. In this third embodiment, the distribution problem is reduced by time division based on the information about the time limit for distribution of the distribution items included in the initial conditions, and a distribution plan is generated for each time after the division. 19 is a functional block diagram showing an example of a delivery planning system according to a third embodiment of the present invention. Among the configurations of the third embodiment of the present invention, the same reference numerals are assigned to the functional portions of the delivery planning device 10B constituting the first embodiment of the present invention, and descriptions thereof are omitted. The delivery planning device 10B according to the third embodiment includes a time division unit 17 instead of the first area division unit 14 having the configuration of the first embodiment. The delivery plan device 10B includes a delivery plan generation unit 12a instead of the delivery plan generation unit 12. The time division unit 17 divides the delivery restriction time given in the initial condition into a plurality of times, and thereby divides the delivery problem into a small-scale delivery problem for each divided delivery time. Each time formed by the time division unit 17 is referred to as a section. The delivery plan generating unit 12 a is a segment formed by the time division unit 17, and solves the delivery problem in which different objective functions or restrictions are set to generate a delivery plan. For example, the delivery plan generation unit 12a generates the delivery status of the delivery items (the progress status of delivery at the end of the previous section) from the first time of each divided section, and starts the delivery in this section. It may be delivered to a distribution plan such as a required distribution base. The last interval among the divisions formed by the time division unit 17 is all the distribution items that will be delivered in the last interval to the necessary distribution bases indicated by the initial conditions, all of which will become undelivered distribution bases. Delivery plan. The time division unit 17 and the delivery plan generation unit 12a are implemented by reading a program from the memory unit 15 and executing it by a CPU included in the delivery plan apparatus 10B. 20 is a first diagram illustrating a time division process of a delivery problem according to a third embodiment of the present invention. The left diagram of FIG. 20 shows the initial state of a certain delivery problem. There are two extra items d1 at the distribution site w1, and three extra items d1 at the distribution site w2. There are less than four items d1 at the distribution site w3, and less than one item d1 at the distribution site w4. It can be considered that from this initial state, the delivery of the delivery d1 becomes a requirement that meets the needs of the delivery site w3 and the delivery site w4 within 120 minutes. In the first embodiment and the second embodiment, the distribution base w1 to the distribution base w4 are divided for each area. In the present embodiment, the delivery time limit of 120 minutes is assigned as the initial condition. Specifically, the time division unit 17 divides the delivery restriction time 120 minutes into plural times (intervals). For example, the time division unit 17 divides the delivery restriction time 120 minutes into two sections of the first half 60 minutes and the second half 60 minutes. The time length or the number of intervals in one interval formed by the time division unit 17 may be arbitrary. For example, the time division unit 17 may divide 120 minutes into 90 minutes and 30 minutes, or classify them into three intervals of 40 minutes. The time division unit 17 may be a time period shorter than the delivery restriction time given in the initial condition by a predetermined time as the first interval after division and the remaining time as the last interval. [0106] The right diagram of FIG. 20 shows that the time division unit 17 divides the delivery restriction time 120 minutes into two intervals of 60 minutes each. Once the time division unit 17 divides the delivery time limit, the delivery plan generation unit 12a generates a delivery plan for the first interval formed by the division. At this time, the distribution plan generation unit 12a does not aim to meet all the requirements, but generates a distribution plan such that it meets as many requirements as possible at the end of one destination interval. The goal is to meet all the requirements. In this case, the distribution item d1 is distributed in 60 minutes, and the required number of distribution sites w3 and w4 can be met. The so-called distribution plan that meets as many requirements as possible, for example, 60 minutes after the start of distribution, the number of items d1 at the distribution point w3 is less than 3, and the number of items d1 at the distribution point w4 is 0. When there are less than two delivery plans and two delivery items d1 at the delivery site w3, when the delivery plan with less than zero delivery items d1 at the delivery site w4 is generated, it means the latter delivery plan. [0107] Next, the objective function and the limitation for the first interval setting will be described. The purpose function described next is more generally the case where the time division unit 17 divides the delivery restriction time into N, except for the last interval (the Nth interval), for all intervals (along the flow of time, from the first 1 interval to N-the first interval) the objective function used. [0108] (Objective Function) Minimize the following sums (1) to (7). (1) The moving cost between sites can suppress the moving cost between sites. (2) The time when the supply is in accordance with the demand When the time when the supply in accordance with the demand is promoted is as fast as possible, the number of solution options will be reduced (although it is the case that the same delivery can be made even at the later time, by only solving the first delivery , Can reduce the choices, and reduce the amount of calculations). (3) Orders that are supplied when the demand meets the requirements. When the orders with smaller numbers are promoted to supply, the number of solution options will be reduced (although there are no problems even if the orders are delivered to larger numbers. (By choosing the order with the smallest number, you can reduce the choice of solution and reduce the amount of calculation). (4) The number of users and distribution means in the distribution base. The number of non-users in the following sections (g [w]) promotes the last moment of the section being calculated, so that the next section is not used. The extra people and the delivery means for the delivery will move to the starting point. For example, at the last moment of the first section, when there is no delivery means that can be moved by a bicycle, in the second section, because the bicycle is not used for delivery, it is moved to the starting point. (5) In the case of meeting the needs of the demand points and the supply of the supply points, the number of people and distribution means at the distribution bases urges that no people or distribution means remain at the distribution bases that meet the needs. In this embodiment, each time zone is divided (although it inherits the delivery status of the previous zone), but the delivery plan is calculated independently. Therefore, there may be redundant delivery staff or delivery methods that are not used in the following zones. Remains at the distribution base. Then, (4) and (5) are added so that excess distribution personnel and the like do not remain at the distribution base. (6) The number of distribution items left at the supply point, the number of distribution items that are insufficient at the need point (7) The number of distribution points that are insufficient for the distribution point By (6), (7), the At the last moment, try to meet as many requirements as possible. The objective function is expressed as a case where the sum of the functions corresponding to each of the items (1) to (7) is minimized. However, each of the items of the objective function (function of each item) may be multiplied by an arbitrary coefficient. To weight. [0109] Next, restrictions will be described. 1. Flow saving rule (I) Cases other than the last one among the divided sections (1) The flow rate of the delivered goods is at the start time of the section, and the flow rate from the stop where there is supply is 1 , The flow from the stop where there is no supply is 0. At other points, it is not the case at the end of the interval, the outgoing traffic is equal to the incoming traffic. (2) The flow rate of the delivery vehicles is the number of delivery vehicles existing at the base at the start time of the section. At other points, it is not the case at the end of the interval, the outgoing traffic is equal to the incoming traffic. (3) The flow of delivery personnel is at the beginning of the interval. The flow of traffic out of the road is the number of delivery personnel who exist at the base. At other points, it is not the case at the end of the interval, the outgoing traffic is equal to the incoming traffic. [0110] (II) Case of the last section among the divided sections (1) The flow rate of the deliverables at the start time of the section, the flow rate from the stop where the supply exists is 1, and the supply never exists The outbound traffic at the stops becomes 0. At the end of the interval, the flow rate to the order where there is a need is 1 and the flow rate to the order where there is no need is 0. At other points, outgoing traffic is equal to incoming traffic. (2) The flow rate of the delivery vehicles is the number of delivery vehicles that exist at the base when the delivery start time of the section is reached. At the end of the interval, the amount of traffic entering from the road is the number of delivery vehicles needed at the base. At other points, outgoing traffic is equal to incoming traffic. (3) The flow rate of the delivery staff is the number of delivery staff at the base when the delivery start time of the section is reached. At the end of the interval, the volume of traffic entering from the road is the number of delivery staff who need it at that location. At other points, outgoing traffic is equal to incoming traffic. [0111] 2. The amount of movement of the items and people in the capacity-restricted distribution base is 1 or less. [0112] 3. Restrictions in Distribution Bases 1 (E _wp (It is a collection of branches, distribution means, and people moving from the road to the stop.) (1) When the place where d goes is d, the delivery does not enter the stop from the road. (2) When the destination of e is the required point of d, the flow rate of the distribution goods and the distribution personnel shall be the same value (0 or 1). (3) In either case, the number of bicycles is less than the number of delivery staff. [0113] 4. Restriction in Distribution Base 2 (E _pw (It is a collection of distribution goods, distribution means, and branches of people moving from the stop to the road.) (1) When the starting point of e is the supply point of d, the flow of the distribution goods and the distribution personnel is the same value (0 or 1). (2) When the starting point of e is the required point of d, the delivery does not go out of the stop to the road. (3) In either case, the number of bicycles is less than the number of delivery staff. [0114] 5. Restriction on the variables of the penalty at the last moment of the section For an arbitrary road w, when the number of people or delivery means not used in the next section is set to g [w], put Enter the limit of g [w] ≦ f [w]. f [w] is an arbitrary number. By adjusting the value of f [w], it is possible to change the number of persons and delivery means that can be allowed to remain in the last situation of the interval. [0115] 6. Restrictions on branching from road to road (1) When branching from road to road is a branch of a car (possibility of carrying a bicycle) It is restricted that there must be a delivery person in the delivery vehicle. The number of passengers is less than the number of passengers, and the number of bicycles that cannot be driven is less than the number of bicycles that can be mounted on the bicycle. (2) The branch from the road to the road is a branch of a bicycle and is a branch on foot. When it is not a branch of a bicycle (moving by bicycle or walking), the sum of the number of bicycles and the number of people moving on foot is equivalent to moving the branch. The number of delivery staff. (3) The branch from the road to the road is a branch of a bicycle, but is not a branch of a car or a branch on foot (moved by a bicycle). The number of bicycles is equal to the number of delivery personnel who move the branch. (4) The branch from the road to the road is a branch on foot, but it is not a branch of a bicycle or a branch of a bicycle (moving on foot). The number of people moving on foot is equal to the number of delivery personnel moving the branch. [0116] 7. The restriction on the branches staying in the distribution base is limited to a certain person in the vehicle, the bicycle cannot be stopped on the road, and the total volume of the distribution is less than the loading capacity of the truck. [0117] The delivery plan generation unit 12a uses the first or second spatiotemporal network to solve the delivery problem (integer plan problem) that is formalized under such objective functions or restrictions. In actual calculations, cutting can also be added to achieve higher speed. An example of a result of the delivery plan generation unit 12a generating a delivery plan for the first interval is shown in the right diagram of FIG. 20. According to this plan, 60 minutes after the start of distribution, there is more than one distribution item d1 at distribution point w1 and distribution point w2, and there are less than two distribution items d1 at distribution point w3 and at distribution point w4. The deficiency of d1 is eliminated. [0118] The advantages of the method of calculating by dividing the time in this way can be regarded as the second point. First, by setting the delivery restriction time from 120 minutes to 60 minutes, the number of parameters necessary for calculation can be reduced, and the amount of calculation can be reduced. In FIG. 20, for convenience of description, an example is shown in which the number of distribution sites and the number of items are small. However, when calculating the distribution of 20 or more distribution items to 20 distribution points within 120 minutes, for example, it can be seen that The variable is 41000 and even limited to 61000. In contrast, when dividing the time in the first half of 60 minutes to produce the above-mentioned distribution plan that meets as many requirements as possible, for example, the number of variables can be reduced to 14,000 and the limited number can be reduced to 18,000. By reducing the number of parameters in this way, the amount of calculation can be reduced and the processing speed can be increased. Next, a description will be given of the process of generating a delivery plan for the second 60 minutes. 21 is a second diagram illustrating a time division process of a delivery problem according to a third embodiment of the present invention. FIG. 21 shows the generation process of the delivery plan using the second half of the 60 minutes after the division. Sort out the required quantity and supply quantity of each distribution base at the start time point of the second half of 60 minutes. At the start point of the second half of the time, there is more than one delivery item d1 at the delivery point w1 and the delivery point w2, and at delivery point w3, there are less than two delivery items d1. The delivery plan generation unit 12a must use the latter half of the 60 minutes to generate the delivery plan in order to deliver the delivery site d1 of the delivery site w1 and the delivery site w2 to meet the needs of the delivery site w3 within the remaining 60 minutes. Regarding the distribution base w4, because the shortage of the distribution base w4 is eliminated in the first half of 60 minutes, it is not included in the distribution problem in the second half of 60 minutes. [0120] Next, a description will be given of an objective function and a restriction set for a delivery problem that targets the last interval when the delivery restriction time is divided into N. The objective function, restriction, and the like in this case are the same as those explained using the first space-time network model (Figure 3) and the second space-time network model (Figure 8). In other words, the delivery plan generation unit 12a generates delivery plans that minimize the cost or travel time of delivery among the delivery plans that fulfill all the requirements until the last time of the last section and meets all needs. plan. [0121] Taking the advantages of the processing in the second half of the 60 minutes (last interval), firstly, as in the first half of the 60 minutes, by setting the delivery restriction time to 60 minutes, the number of parameters can be reduced and the amount of calculation can be reduced. This makes it possible to increase the speed of processing. Furthermore, it is possible to calculate as many distribution plans as possible in each section up to the last section, and the remaining requirements will be reduced, so the scale of the distribution problem that must be solved will be smaller. For example, in the examples shown in FIG. 20 and FIG. 21, it is not only that the required number of each required point is reduced, which meets the need at the distribution site w4, so the number of distribution sites is reduced. This can further reduce the scale of the distribution problem. Divide the problem of delivering more than 20 deliveries to 20 distribution bases within 120 minutes into 60-minute intervals. In the second 60-minute interval, for example, you can reduce the number of variables to 8000 and limit the number. Reduced to 12000. As described above, according to this embodiment, the reduction of the parameters of time division and the distribution plan generated in the time interval earlier can reduce the scale of the distribution problem in the subsequent interval, so that Speeding up the generation of delivery plans. In the third embodiment, since the area is not divided, compared with the first embodiment and the second embodiment, it is possible to generate a distribution plan while still ensuring the large-scale distribution of the distribution bases, and to produce a more optimized distribution. plan. [0122] Next, a flow of the generation process of the delivery plan according to this embodiment will be described. 22 is a flowchart showing an example of a delivery plan generation process according to the third embodiment of the present invention. The same processing as in FIGS. 13 and 18 will be briefly described. First, a delivery person who performs a delivery plan inputs initial conditions of the delivery plan to the delivery plan device 10B. The input / output unit 13 receives the input, and outputs the received information to the initial condition setting unit 11. The initial condition setting unit 11 acquires information on initial conditions input by the delivery person (step S11). Next, the time division unit 17 performs time division processing using the delivery restriction time included in the information of the initial conditions (step S122). The time division processing is as described using FIG. 20. For example, the time division unit 17 divides the delivery time limit of the initial conditions into two to three. Or, if the time required to complete the distribution of the necessary distribution bases is estimated by a rule of thumb, such as 75 minutes, the time division unit 17 can also use the time unit (based on user settings) ( For example, 75 minutes) to divide the original delivery limit time, and use the remaining time as the final interval. Alternatively, the time division unit 17 may be a time period shorter than the delivery restriction time given in the initial condition by a predetermined time as the first interval after division and the remaining time as the last interval. Next, the delivery plan generation unit 12a generates a delivery plan in chronological order for each divided section. First, the delivery plan generation unit 12a sets 1 to a counter variable n (step S123). Next, the delivery plan generation unit 12a sets a delivery problem for the n-th section (step S124). For example, if it is the first section, the delivery plan generation unit 12a includes the required number and supply amount of each delivery site included in the information of the initial conditions, the number of delivery means existing at the departure site, and the number of delivery staff. 1. The time of the first interval is used for the delivery limited time, which meets as many requirements as possible, and formulates the integer planning problem of the objective function and restriction conditions for the production of the cheapest delivery plan. [0123] Next, the distribution plan generation unit 12a generates a plurality of time-space network models exemplified in FIG. 3 or FIG. A collection of branch information that may satisfy the needs of each distribution base (step S132). Next, the delivery plan generation unit 12a calculates the total cost for each set of branch information generated (step S14). Next, the delivery plan generation unit 12a compares the calculated total cost and selects a set of branch information whose total cost is the smallest (step S15). As a result, a delivery plan for the nth (this time the first) interval will be generated. [0124] Next, the delivery plan generation unit 12a determines whether n is equal to N (step S16). When n is equal to N (step S16; Yes), the delivery plan is generated for all the segments after the division, and therefore the delivery plan generation process is terminated. When n is not equal to N (step S16; No), the delivery plan generation unit 12a adds 1 to n (step S17), and repeats the processing from step S124. [0125] Specifically, for example, when the value of n after adding 1 is 2, the delivery plan generating unit 12a is the result of each of the results after executing the delivery plan generated for the first interval in step S124. The number of required distribution points, the number of supply points, the number of distribution means existing at the starting point, the number of distribution personnel, and the time in the second interval are used for the time limit for distribution, which formalizes the integer planning problem. At this time, if n and N are equal, the delivery plan generation unit 12a formulates the objective function for generating delivery plans that meets all the requirements, and the integer plan problem of constraints (as in the first embodiment and the second embodiment). The same objective function and the like of the implementation form). When n is not equal to N, the delivery plan generation unit 12a formulates an objective function for generating a delivery plan that meets as many requirements as possible, and an integer plan problem with restrictions. The delivery plan generation unit 12a solves the integer plan problem and generates a delivery plan for the n-th interval. The delivery plan generation unit 12a repeats the processing from step S124 to step S17 for all sections until a delivery plan is generated (until n and N are equal). The entire distribution plan that is sequentially generated for each of the first to Nth (last) sections is a distribution plan that meets the requirements given in the initial conditions. [0126] In the flowchart of FIG. 22, the delivery restriction time initially given in the initial condition is divided into several sections, and for example, the delivery planning process may be configured as follows. 1. First, a section (first delivery restriction time) shorter than the delivery restriction time given in the initial condition is set, and as many delivery plans as possible within this interval can be produced cheaply. 2. Secondly, for the delivery items that cannot be delivered within the first delivery restriction time, a predetermined length interval (second delivery restriction time) that continues to the first delivery restriction time is set to produce as much as possible within the set interval. Delivery plan for multiple delivery items. 3. The total length of the interval from the start of delivery will not exceed the period of delivery limit time. Repeat steps 1. to 2. That is, the solution is found while extending the time (time expansion method). The length of the first section or extended section can be arbitrarily set according to the delivery status. 4. When the total time from the delivery start time exceeds the delivery limit time, the next interval will be used as the last one, and the last interval will be generated. The start time of the time is used as a reference, and the time when the delivery restriction time included in the initial conditions is used as the end time) is a delivery plan that meets all the required costs to the minimum. [0127] When the distribution plan generation processing of this embodiment is actually performed, for a distribution problem with 20 distribution bases and 20 levels of distribution items, a practically optimal time (within 10 minutes) can be used to calculate a quasi-optimal solution (with strict (Comparison of the optimal solution of., The difference between the values of the objective function is less than 10%). [0128] The method for generating a delivery plan according to this embodiment can also be used in the following scenarios. For example, when all vehicles must be delivered to a parking lot in need within 120 minutes, a delivery plan is first generated for the first 60 minutes. Once the delivery plan is completed, the vehicle delivery is actually started based on the delivery plan. While the vehicle is being delivered, the remaining 60-minute delivery plan is generated. In this way, by generating and processing a parallel delivery plan, for example, time can be effectively used at a site where a car sharing service is performed. [0129] The processes of the above-mentioned distribution planning devices 10, 10A, and 10B are stored in a computer-readable recording medium in the form of a program, and the program is read out and executed by the computer of the distribution planning system. The above processing. The computer-readable recording medium herein means a magnetic butterfly, an optical magnetic disk, a CD-ROM, a DVD-ROM, a semiconductor memory, and the like. This computer program can also be distributed to a computer through a communication line, and the computer that accepts this distribution executes the program. [0130] The above program may be a part for realizing the aforementioned functions. Furthermore, a combination of the aforementioned function and a program that has been recorded in a computer system can be used to implement the so-called differential file (differential program). The delivery plan devices 10, 10A, and 10B may be constituted by a single computer, or may be constituted by a plurality of computers that are communicably connected. [0131] In addition, the constituent elements of the above-described embodiments may be appropriately replaced with well-known constituent elements without departing from the spirit of the present invention. The technical scope of this invention is not limited to the embodiments described above, and various changes can be made without departing from the spirit of the invention. [0132] A delivery person is an example of a delivery subject, a delivery vehicle, a truck, and a bicycle are examples of a delivery means, and a car shared by a vehicle is an example of a delivery item. The first region division unit 14, the second region division unit 16, and the time division unit 17 are examples of the division unit, respectively. [Industrial Applicability] [0133] According to the above-mentioned distribution planning system, distribution planning method, and program, a practical time can be devised to minimize the cost or moving time relative to large-scale distribution problems. A personalized delivery plan.

[0134]

10, 10A, 10B ‧‧‧ Delivery plan device

11‧‧‧Initial condition setting section

12, 12a‧‧‧ Delivery plan generation department

13‧‧‧I / O Department

14‧‧‧ first area division

15‧‧‧Memory Department

16‧‧‧Second Region Division

17‧‧‧Time Division

[0025] FIG. 1 is a functional block diagram showing an example of a delivery planning system according to a first embodiment of the present invention. 2 is a diagram illustrating an example of a delivery plan according to the first embodiment of the present invention. 3 is a diagram illustrating a first spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. 4 is a first diagram illustrating a second spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. 5 is a second diagram illustrating a second spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. 6 is a third diagram illustrating a second spatiotemporal network model of a delivery plan according to the first embodiment of the present invention. 7 is a fourth diagram illustrating a second spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. 8 is a fifth diagram illustrating a second spatio-temporal network model of a delivery plan according to the first embodiment of the present invention. 9 is a diagram showing an example of a delivery problem in the first embodiment of the present invention. FIG. 10 is a diagram showing an example of a delivery plan for a delivery problem. 11 is a first diagram illustrating a first region dividing process according to the first embodiment of the present invention. FIG. 12 is a second diagram illustrating a first region dividing process according to the first embodiment of the present invention. FIG. 13 is a flowchart showing an example of a delivery plan generation process according to the first embodiment of the present invention. 14 is a functional block diagram showing an example of a delivery planning system according to a second embodiment of the present invention. FIG. 15 is a first diagram illustrating a second region division process of a delivery problem according to a second embodiment of the present invention. FIG. 16 is a second diagram illustrating a second region division process of a delivery problem according to a second embodiment of the present invention. 17 is a third diagram illustrating a second region division process of a delivery problem according to a second embodiment of the present invention. FIG. 18 is a flowchart showing an example of a delivery plan generation process according to the second embodiment of the present invention. 19 is a functional block diagram showing an example of a delivery planning system according to a third embodiment of the present invention. FIG. 20 is a first diagram illustrating a time division process of a delivery problem according to a third embodiment of the present invention. FIG. 21 is a second diagram illustrating a time division process of a delivery problem according to a third embodiment of the present invention. FIG. 22 is a flowchart showing an example of a delivery plan generation process according to the third embodiment of the present invention.

Claims (15)

A distribution planning system including: (1) a division section that divides the distribution problem indicated by the initial conditions into smaller-scale distribution problems in the distribution problem of distributing items to a distribution point in need; and The delivery plan generating unit generates a delivery plan for a delivery problem divided by the aforementioned dividing unit. For example, in the distribution planning system of the first scope of the application for patent, the division section is a demand point included in a distribution base group that requires the distribution item, and a distribution base group that becomes a supply source of the distribution item. The included supply points are attached in such a way that the moving time from the one need point to the one supply point is minimized, and a set of the corresponding combination of the aforementioned need point and the aforementioned supply point is generated, The distribution problem indicated by the initial conditions is divided into a distribution problem from a required point group contained in the generated set to a supply point group. For example, the distribution planning system in the second scope of the patent application, wherein the aforementioned division section calculates the correspondence between the plural supply points and the plural need points contained in the generated set, from one supply point to one. The travel time of the required point from the supply point to the required point is below the predetermined value. The distribution plan generation unit uses the distribution path from the supply point group contained in the generated set to the required point group. The intermediate moving time becomes a distribution path below the predetermined threshold to generate a distribution plan for the aforementioned small-scale distribution problem. For example, in the delivery plan system of the scope of application for the patent, the above-mentioned division unit obtains a plurality of pre-set delivery means that indicates that a part of the delivery bases are dispatched from the departure base and returned to the departure base. The route and the unit route information of the cost at the time of distribution of the distribution route are used to calculate the combination of the plurality of unit route information. The number of the distribution bases contained in the combination is within a predetermined number, and the total of the aforementioned costs is minimized. The combination of the starting point and the distribution point included in the combination is generated, and the distribution problem shown in the foregoing initial conditions is divided into the required point group contained in the generated set of the starting point and the distribution point to the supply point group. Shipping issues. For example, the distribution planning system in the fourth scope of the patent application, wherein the aforementioned division unit calculates a combination of the aforementioned unit path information by a row generation method. For example, the distribution planning system of the first scope of the patent application, wherein the aforementioned division section divides the distribution restriction time of the distribution item into a plurality of times, and divides the distribution problem shown in the foregoing initial condition into each of the foregoing The distribution problem of the divided time, the distribution plan generation unit is based on the distribution status of the distribution item at the first time of the divided time to generate the distribution item as much as possible in the divided time. It is often delivered to a distribution plan such as a required base. For example, the delivery plan system of the sixth scope of the application for a patent, wherein the delivery plan generation unit is related to the delivery problem at the last time that is divided by the division unit, and the delivery plan generation unit is to the delivery object until the end of the last time. The delivery plan will be generated to all the necessary delivery bases indicated by the aforementioned initial conditions. For example, the distribution planning system in the first scope of the patent application, wherein the aforementioned division section divides the distribution problem indicated by the aforementioned initial conditions into: The first delivery restriction time is a new delivery restriction time. The aforementioned delivery plan generation unit generates: as many times as possible, the aforementioned delivery items are delivered to a required base or the like within the aforementioned first delivery restriction time. Delivery plan. For example, the distribution planning system of the eighth patent application scope, wherein: the aforementioned division section is to set a predetermined length of time following the first distribution restriction time as the second distribution restriction time; the aforementioned distribution plan generation section is Generated: within the second delivery restriction time, the aforementioned delivery items are delivered to as many delivery plans as needed to as many locations as possible. For example, the delivery plan system of the patent application scope item 8 or 9, wherein the aforementioned delivery plan generating unit is to generate the start time at the end time point when the aforementioned delivery plan is implemented, and use the aforementioned first delivery restriction. The start time of the time is used as a reference, and the time when the delivery restriction time included in the initial conditions mentioned above is used as the final time. As a result of the implementation of the delivery plan, the unfinished delivery is completed. plan. According to the delivery plan system described in any one of claims 6 to 10 in the scope of the patent application, the delivery is performed when as many delivery items as possible are delivered to a required location, such as the aforementioned delivery plan. The plan generation unit generates the delivery plan on the condition that the delivery personnel and delivery means necessary for the execution of the delivery plan do not remain in the delivery base as a result of the execution of the delivery plan. According to the distribution planning system described in any one of claims 1 to 11, the aforementioned distribution planning generation unit is an integer that unpacks a space-time network model composed of point information and branch information. The planning problem generates at least one set of branch information of the distribution related to the distribution problem after the division by the division section. This point information will indicate the distribution main body that distributes the distribution item and the movement of the distribution item or the distribution item. The starting point of the initial position of the main delivery means and the aforementioned delivery point are grouped with each time based on the start of delivery. The branch information is between the two pieces of point information indicating the delivery of the delivery item among the aforementioned point information. Of the aforementioned distribution items, the aforementioned distribution entities, and the aforementioned distribution means involving the aforementioned distribution. For example, the distribution plan system of the 12th scope of the patent application, wherein the aforementioned distribution plan generation unit is based on the aforementioned spatio-temporal network model and generates for one of the aforementioned distribution sites: the entrance and time of the distribution site are set to The point information related to the entry point, the point information related to the exit where the exit point and time of the distribution base are grouped, and the time point related to the distribution item for each of the distribution items related to the distribution base. The point information of the storage place: the flow of the distribution subject and the distribution between the point information related to the aforementioned entrance and the point information related to the aforementioned distribution, and between the point information related to the aforementioned exit and the point information related to the aforementioned distribution. Set the value to 0 or 1. A distribution planning method is characterized by: (1) The distribution planning system is used to divide the distribution problem shown in the initial conditions into smaller-scale distribution problems in the distribution problem of distributing the distribution items to the required distribution bases. The aforementioned divided distribution problem generates a distribution plan. A program that uses the computer of the distribution planning system to function as the following means: In the distribution problem of distributing items to a distribution point where it is needed, the distribution problem shown in the initial conditions is divided into smaller scales The means of distribution problems: (1) Means of generating a distribution plan for the aforementioned divided distribution problems.